IIT-Indore Develops Smart Drones To Detect Anomalies In Structures Like High-Tension Wires, Gas Pipelines & Buildings

IIT-Indore Develops Smart Drones To Detect Anomalies In Structures Like High-Tension Wires, Gas Pipelines & Buildings

The project is led by Prof. Abhirup Datta, along with a student Kumar Shashank Shekhar and Ph.D. scholar Harsha Avinash Tanti.

Staff ReporterUpdated: Tuesday, September 10, 2024, 03:02 PM IST
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Indore (Madhya Pradesh): IIT Indore has developed a cutting-edge system that integrates Unmanned Aerial Vehicles (UAVs) with Artificial Intelligence (AI) and Machine Learning (ML) to inspect and detect anomalies in structures, especially in difficult-to-reach areas. This innovative system uses AI-ML technology to identify and classify cracks and other anomalies in structures such as high-tension wires, buildings, and roads in real-time.

Traditional inspection methods often struggle with accurately detecting these issues, particularly in complex environments. The project is led by Prof. Abhirup Datta, along with a student Kumar Shashank Shekhar and Ph.D. scholar Harsha Avinash Tanti.

Prof. Suhas Joshi, Director IIT Indore said “This technology is particularly valuable for inspecting extensive road networks, cross-country gas pipelines, and high-tension power transmission lines. It has massive applications in maintenance and surveillance of infrastructures like roads, power lines, etc., as well as in defence and space.”

Prof. Datta said “The system has shown remarkable accuracy, achieving a 98.7% success rate in detecting and classifying cracks and processing data in just 25 milliseconds using advanced AI edge devices like NVIDIA Jetson. With its wide range of applications, including security and surveillance, this AI-enabled UAV system is set to become an essential tool in ensuring the safety and longevity of critical infrastructure

UAV's loaded with latest tech

The UAVs are equipped with advanced cameras and LiDAR sensors, which together provide detailed information about the location and size of any detected anomalies. One of the key features of this system is its ability to process data directly on the drone using edge computing, allowing for real-time decision-making. The drone's payload has been optimized to minimize space and power consumption, ensuring high performance and efficiency.

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